foldseek-structural-search▌
google-deepmind/science-skills · updated Jun 4, 2026
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### Foldseek Structural Search
- ›name: "foldseek-structural-search"
- ›description: "Performs 3D structural searches of proteins against various databases (PDB, AlphaFold, CATH, MGnify, etc.) using the Foldseek API. Use ONLY when the user provides a physical 3D coordinate file (.cif, ..."
| name | foldseek-structural-search |
| description | > Performs 3D structural searches of proteins against various databases (PDB, AlphaFold, CATH, MGnify, etc.) using the Foldseek API. Use ONLY when the user provides a physical 3D coordinate file (.cif, .mmcif, or .pdb) and wants to find structurally similar proteins. Do NOT use if the user only provides a protein sequence, gene name, or UniProt ID. |
Prerequisites
uv: Read theuvskill and follow its Setup instructions to ensureuvis installed and on PATH.- User Notification: If LICENSE_NOTIFICATION.txt does not already exist in this skill directory then (1) prominently notify the user to check the terms at https://search.foldseek.com/search and https://github.com/steineggerlab/foldseek, then (2) create the file recording the notification text and timestamp.
Goal
Submit a user-provided 3D protein structure file (.cif, .mmcif, or .pdb)
to the Foldseek web server API to find structurally similar proteins. Report the
top structural hits, interpret key alignment metrics, summarize the inferred
protein functions, save the Markdown-formatted table to a .md file, and save
the full detailed results to a local JSON file.
Core Rules
- File Requirement: This tool absolutely cannot search by sequence, name,
or accession ID. It strictly requires a
.pdb,.cif, or.mmciffile path. - Strict Validation: Never bypass the input validation or the database allowlist check.
- Do Not Parse the JSON: Rely entirely on the generated
.mdfile for your immediate summary. The JSON is saved purely for subsequent, specialized tool use. - No Raw Parsing: Do not attempt to parse or read the raw 3D coordinates yourself; always pass the file to the script.
- Notification: If this skill is used, ensure this is mentioned in the output.
Instructions
- Strict Input Validation: Verify that the user has explicitly provided a
valid path to a
.cif,.mmcif, or.pdbfile in their workspace.- If the user provided a protein name, an amino acid sequence, or an accession ID (e.g., a UniProt ID) but NO downloaded structure file, halt immediately. Do not run the script.
- Inform the user that Foldseek requires a physical 3D coordinate file, and suggest downloading the structure first (e.g., using the AlphaFold fetch tool).
- Database Validation: Check if the user requested specific databases to
search.
- Allowed List:
afdb50,afdb-swissprot,pdb100,BFVD,mgnify_esm30,cath50,gmgcl_id,bfmd,afdb-proteome. - If the user requests a database NOT on this list, halt immediately. Do not run the script. Inform the user that the database is unsupported and provide them with the allowed list.
- Allowed List:
- Generate File Names: Generate descriptive output file names for both the
JSON data and the Markdown table based on the input file (e.g.,
proteinA_foldseek_results.jsonandproteinA_foldseek_results.md). - Execute the python script based on the user's request, redirecting the
standard output into your generated
.mdfile:- Default (No databases specified):
uv run scripts/search.py <path-to-file> -o <generated-filename.json> > <generated-filename.md> - Custom (Valid databases specified):
uv run scripts/search.py <path-to-file> -o <generated-filename.json> --databases <db1,db2,db3> > <generated-filename.md>
- Default (No databases specified):
- The script will query the databases, save the full JSON payload, and write a
Markdown-formatted table to your specified
.mdfile. - Read the Results: Open and read the newly generated
.mdfile carefully to view the Markdown table. - Interpret the Metrics: Summarize the top 3 to 5 structural matches that
have meaningfull annotations for the user. When reporting, assess the match
quality using these specific fields:
- Prob (Probability): Values approaching 1.0 (100%) indicate extreme confidence that the fold is a true structural homologue.
- Q-Cov (Query Coverage): High percentages mean the match covers the majority of the query protein's overall shape, rather than just a small local motif.
- E-value & Seq Identity: Use these to provide additional evolutionary context.
- Perform Functional Analysis: Analyze the text descriptions embedded
within the
Target IDcolumn for the reported matches.- Explicitly report the specific protein names/functions of the top structural homologues.
- Provide a synthesized overview summarizing the entire variety of different functions, domains, or protein families found across the whole list of homologues (e.g., "Most hits are portal proteins, but there is also a distinct cluster of viral capsid matches...").
- Explicitly inform the user of both newly created files (
.jsonand.md) and their locations so they can be seamlessly used in subsequent analysis steps.
* If the API returns an error or the file is missing, inform the user clearly
and ask them to verify the file path.
How to use foldseek-structural-search on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add foldseek-structural-search
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches foldseek-structural-search from GitHub repository google-deepmind/science-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate foldseek-structural-search. Access the skill through slash commands (e.g., /foldseek-structural-search) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★73 reviews- ★★★★★Fatima Verma· Dec 28, 2024
foldseek-structural-search fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Kiara Mehta· Dec 28, 2024
We added foldseek-structural-search from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Yusuf Mehta· Dec 24, 2024
foldseek-structural-search reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Liam Torres· Dec 24, 2024
Useful defaults in foldseek-structural-search — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Diego Chen· Nov 19, 2024
foldseek-structural-search is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Noor Garcia· Nov 19, 2024
Useful defaults in foldseek-structural-search — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Rahul Santra· Nov 15, 2024
Keeps context tight: foldseek-structural-search is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Yusuf Reddy· Nov 15, 2024
Registry listing for foldseek-structural-search matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Kwame Li· Nov 15, 2024
We added foldseek-structural-search from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Noor Thompson· Oct 10, 2024
Solid pick for teams standardizing on skills: foldseek-structural-search is focused, and the summary matches what you get after install.
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